Data Warehouse Certification Training

Data Warehousing Certification Training

A Self-Paced course designed to give you a head start into Data warehousing and train you on different concepts of Data warehousing along with the implementations of these concepts.

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Data Warehousing Certification Training UpComing Batches

Nov-22 - Jan-03

Weekend
SOLD OUT

Timings: 07:00 AM To 10:00 AM (IST)

350.00     Enroll Now

Nov-15 - Dec-27

Weekday
SOLD OUT

Timings: 20:30 PM To 23:30 PM (IST)

350.00     Enroll Now

Dec-04 - Jan-15

Weekend
FILLING FAST

Timings: 07:00 AM To 10:00 AM (IST)

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Dec-11 - Jan-22

Weekday
FILLING FAST

Timings: 20:30 PM To 23:30 PM (IST)

350.00     Enroll Now

Dec-18 - Jan-29

Weekend

Timings: 07:00 AM To 10:00 AM (IST)

350.00     Enroll Now

Dec-25 - Feb-05

Weekday

Timings: 20:30 PM To 23:30 PM (IST)

350.00     Enroll Now
Be future ready. Start learning
Structure your learning and get a certificate to prove it.
Start Learning

Course Curriculum

Data Warehousing Certification Training

SELF PACED

A Self-Paced course designed to give you a head start into Data warehousing and train you on different concepts of Data warehousing along with the implementations of these concepts.

  • WEEK 5-6
  • 10 Modules
  • 6 Hours
Data Warehouse Along With The Implementations

Learning Objectives - Discussing about the basic concepts of a data warehouse and why it is needed. Difference between an operational system and an analytical system, Datamarts. Approaches to build a data warehouse.

Topics : 

  • What is a Data Warehouse?
  • Definition and Explanation of the Four Terms.
  • Subject Oriented.
  • Integrated.
  • Non Volatile and Time Variant.
  • Need for a Data Warehouse.
  • Difference between a Database and a Data Warehouse.
  • OLTP and OLAP?
  • Datamart - The smaller cousin of the Data Warehouse.
  • ODS - Operational Data Store.
  • Definition and Explanation of 4 terms - Subject Oriented, Integrated, Current, Volatile, Detailed.
  • Benefits of ODS.
  • Design Approach - Top Down Approach, Bottom up Approach, Federated.

Learning Objectives - Learning what a dimension and a fact is, the different types of dimensions and facts. Reporting concept of Hierarchy.

Topics :

  • Dimensions and Facts.
  • What are Dimensions and Facts?
  • Types of Dimensions - Emphasis on SCD 1,2,3 Implementations.
  • Types of Facts.
  • What are Hierarchies?
  • Types of Hierarchies.

Learning Objectives - Organizing data in multiple tables. Understanding normalization and its different forms. Learning what is a schema and the different types of schemas along with meta data.

Topics :

  • Normalization.
  • Schemas.
  • What is a Schema?
  • Types - Star, Snowflake, Galaxy.
  • Significant Role of Meta Data.

Learning Objectives - Understanding principles of requirement gathering to build a warehouse and dimensional modeling.

Topics :

  • Requirement Gathering.
  • Principles of Dimensional Modelling.
  • Modeling - ER Diagrams.


Learning Objectives - Understanding where will the data come from and how will the data come and Populating the warehouse.Learning concepts of Extracting data, Transforming data and Loading the data into different tables.

Topics :

  • ETL Concept - Architectural Components - like Source, Staging, Atomic, Dimension.
  • Transformation - Data Validation.
  • Data Accuracy.
  • Data Type Conversion.
  • Business Rule Application.
  • Data Loading Techniques.


Learning Objectives - Implementing a data warehouse Project.

Topics :

  • Discuss Project and its Problem Statement.
  • Probable Solutions and Implement One Solution.

Program Syllabus

Curriculum

You can also view the program syllabus by downloading this program Curriculum.

Projects

Which case studies will be the part of this course?

Creation of Sales Data Warehouse & Data MartsIndustry, Retail Data, North-wind/Adventure Works dataset. Problem Statement: Creation Sales Data Mart using erwin r9

What are the pre-requisites for this course?

The pre-requisites for this course include basic knowledge of SQL, General Relational Database (Oracle), Microsoft Windows GUI, Basic Unix, Windows Command line.

How will I execute the practicals?

For doing the practicals we will help you to setup erwin r9, Talend 5.x and Tableau 9.x. The detailed installation guides are provided in the LMS for setting up the environment. In case you come across any doubt, the 24*7 support team will promptly assist you.

Course Description


Objectives Of Our Online PySpark Training Course
Course Objectives After the completion of Data warehousing course at OL Tech Edu, you will be able to:
  • Understand the concept and need of Data warehouse.
  • Implement concepts of dimension and fact table.
  • Implement data modelling, normalization and schema concepts.
  • Model a Data warehouse.
  • Implement ETL jobs.

Course Certification

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Course FAQ's

Features

Explore step by step paths to get started on your journey to Jobs of Today and Tomorrow.

Instructor-led Sessions

30 Hours of Online Live Instructor-Led Classes.
Weekend Class : 10 sessions of 3 hours each.

Real Life Case Studies

Real-life Case Studies

Live project based on any of the selected use cases, involving implementation of the various real life solutions / services.

Assignments

Assignments

Each class will be followed by practical assignments.

24 x 7 Expert Support

24 x 7 Expert Support

We have 24x7 online support team to resolve all your technical queries, through ticket based tracking system, for the lifetime.

Certification

Certification

Towards the end of the course, OL Tech Edu certifies you for the course you had enrolled for based on the project you submit.

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